Regression Basics

Interactive courseware module that addresses the fundamentals of regression analysis taught in STEM courses.
Updated 20 Nov 2023

Regression Basics

View on File Exchange or Open in MATLAB Online

MATLAB Versions Tested

Curriculum Module

Created with R2020a. Compatible with R2020a and later releases.


This curriculum module contains an interactive MATLAB® live script that illustrates some basic concepts of regression analysis.


You can use this live script as a demonstration in lectures, a class activity, or an interactive assignment outside class. This module covers topics including solving for linear regression parameters, assessing and improving performance of regression models, and applying the gradient descent algorithm. It also includes an example of using a linear regression model to perform short-term forecasting.

The instructions inside the live script will guide you through the exercises and activities. Get started with the live script by running it one section at a time. To stop running the script or a section midway (for example, when an animation is in progress), use the image_0.png Stop button in the RUN section of the Live Editor tab in the MATLAB Toolstrip.

Contact Us

Solutions are available upon instructor request. Contact the MathWorks teaching resources team if you would like to request solutions, provide feedback, or if you have a question.


This module assumes knowledge of plotting and working with linear data.

Getting Started

Accessing the Module

On MATLAB Online:

Use the image_1.png link to download the module. You will be prompted to log in or create a MathWorks account. The project will be loaded, and you will see an app with several navigation options to get you started.

On Desktop:

Download or clone this repository. Open MATLAB, navigate to the folder containing these scripts and double-click on RegressionBasics.prj. It will add the appropriate files to your MATLAB path and open an app that asks you where you would like to start.

Ensure you have all the required products (listed below) installed. If you need to include a product, add it using the Add-On Explorer. To install an add-on, go to the Home tab and select image_2.png Add-Ons > Get Add-Ons.


MATLAB® is used throughout. Tools from Statistics and Machine Learning Toolbox™ are used frequently as well.


If you are viewing this in a version of MATLAB prior to R2023b, you can view the learning outcomes for each script here

image_3.png In this script, students will...
- Use least squares to solve for linear regression paramaters
- Use a goodness-of-fit measure to assess model performance
- Apply a basic linear regression to model real-world electricity load data

Related Courseware Modules

image_4.png Available on:image_5.pngimage_6.pngGitHub

image_7.png Available on:image_8.pngimage_9.pngGitHub

Or feel free to explore our other modular courseware content.

Educator Resources


Looking for more? Find an issue? Have a suggestion? Please contact the MathWorks teaching resources team. If you want to contribute directly to this project, you can find information about how to do so in the page on GitHub.

© Copyright 2023 The MathWorks™, Inc

Cite As

Chad Allie (2024). Regression Basics (, GitHub. Retrieved .

MATLAB Release Compatibility
Created with R2020a
Compatible with R2020a and later releases
Platform Compatibility
Windows macOS Linux
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Version Published Release Notes

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See release notes for this release on GitHub:


See release notes for this release on GitHub:


See release notes for this release on GitHub:


See release notes for this release on GitHub:


See release notes for this release on GitHub:


To view or report issues in this GitHub add-on, visit the GitHub Repository.
To view or report issues in this GitHub add-on, visit the GitHub Repository.